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Duke Energy Carbon-Free Resource Integration Study

Duke Energy has partnered with the National Renewable Energy Laboratory (NREL) to evaluate pathways to achieving their carbon-free targets and to assess the operational impacts of the resulting system. This report details findings from Phase II of the Duke Low Carbon Resource Integration study, which consisted of three separate but interrelated analyses: (1) a resource assessment exploring the technical and economic potential and characteristics of wind and solar resources in the Carolinas; (2) capacity expansion modeling identifying the least-cost investment pathways for achieving 70% CO 2 emissions reductions in North Carolina by 2030 and a net-zero electricity system by 2050; and (3) detailed production cost modeling of power system operations at the higher shares of low- and zero-carbon emitting generation sources, informed by the capacity expansion modeling portion of the analysis. The analysis finds that Duke Energy can approach the 2030 and 2050 emissions target in North Carolina through investment in a combination of solar, wind, and storage along with maintaining its existing nuclear fleet. The average cost of CO 2 abatement in the Carolinas through 2021-2050 is on the order of $\$27-33$ per metric ton (range of $\$9-34$ per metric ton across key sensitivities).Duke Energy can expected increased interchange with neighbors to help balance higher levels of solar, although the ability to do this will depend on whether neighboring regions also move to integrate more carbon-free resources. As Duke Energy moves toward both the 2030 and 2050 targets, addressing energy needs during the winter peak period becomes particularly important, and the system relies on the availability of resources such as renewable or hydrogen combustion turbines, seasonal storage, or other similar technologies that are dispatchable but able to operate at low capacity factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals

Using Japan as a proxy for a developed nation, we investigated the role of existing and nascent technologies in curbing carbon emissions. We simulated possible pathways to meeting 2030 and 2050 emission targets within the Japanese electricity supply sector using a single-region model in The Integrated MARKAL-EFOM System (TIMES). Critically, our simulations incorporate novel technologies like hydrogen electrolysers, carbon capture, photochemical water splitting, and emerging photovoltaic cells, assess long-term impacts up to the year 2100, and include life-cycle emissions and learning curves for parameters such as investment cost, efficiency, and emission coefficients. Results indicate that a hybrid approach, using nuclear power and hydrogen from renewable energy-based electrolysis, is cost-effective and provides long-term emission reduction along with energy security. Finally, nuclear, wind, solar, and hydrogen from renewables emerge as key emission reduction technologies, while natural gas with carbon capture plays a minor role in achieving emission reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Mexico and U.S. Power Systems Under Variations in Natural Gas Prices

This study examines the impact of natural gas prices on the power systems of Mexico and the United States. For this, we develop an integrated modeling framework by soft linking three different techno-economic bottom-up models of the power and energy systems, one partial equilibrium model of the natural gas sector, and a partial equilibrium model of the Mexican energy sector. Our results show several interesting results: high natural gas prices raise the use of carbon-intensive technologies in the short-term and boost renewable investments at longer time intervals, increasing emissions in earlier periods and reducing them thereafter. Regarding system costs, because of more capital-intensive green power and lower expenditures in raw energy carriers, capital costs rise and operating costs decrease in the long haul. Furthermore, we see an increase in natural gas demand when its price is low, reducing long-term capital and operating costs through cheaper energy inputs in natural gas facilities and a lower share of capital-intensive renewable facilities in the power system. Concerning emissions, low natural-gas prices decrease coal use in the United States, reducing anthropogenic emissions until the last stages of the optimization period. For Mexico, they show heterogeneous results across models. Policymakers can use this study's results to understand the influence of natural gas prices in the Mexican and United States energy sectors.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗

GRAF-Plan for Vietnam

Evaluates the reserve requirements for power system balancing areas based on variability and uncertainty of load as well as wind and solar generation scenarios. The tool uses minute‐by‐minute site‐specific generation and load information, as well as information from generation and load forecasting algorithms used in the balancing areas. The Balancing‐Plan Tool can be used directly by utility planners and operators to aid in the integration of intermittent renewable resources. The tool provides reserve requirements of various kinds, such as day‐ahead, load following and regulation, as well as estimates the capacity of the generation fleet to provide the require reserves.

Campbell, Allison↗

Advance Distribution Management System (ADMS)

This presentation explores the transition from traditional distribution management systems to Advanced Distribution Management Systems (ADMS) as a foundation for smart grid development. It highlights the key benefits of ADMS, including enhanced reliability, improved operational efficiency, and increased situational awareness. The presentation also addresses common implementation challenges such as system integration, data management, and organizational readiness. It concludes with a forward-looking perspective on the evolving role of ADMS and essential takeaways for utilities and stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗

EVSE Cybersecurity and Resilience

Consequence-driven Cybersecurity Analysis for Extreme Fast Charging Electric Vehicle Infrastructure Electric vehicle (EV) development and associated charging infrastructure are expected to advance rapidly. Thirty percent of all global vehicle sales may be EVs and hybrid EVs by 2025, and they will rely on increasingly sophisticated strategies for grid integration. Next-generation EV charging infrastructure is expected to include interconnected renewable resources, such as photovoltaic (PV) arrays and battery storage systems, along with grid-edge devices. Although distributed energy resources (DERs) are useful in several ways, such as peak shaving at high demand times and backup supply for added resilience, the integration of vehicle charging and DERs could create more avenues for cyberattack. Physical and/or remote access to EV charging station components, including charge ports, power electronics, controllers, and local generation (e.g., PV and energy storage) could be paths to cause power fluctuations, leading to altered operations at the charging station, escalated privileges to administrative systems, exfiltration of financial information (including personally identifiable information), and reduced grid stability. One compromised EV supply equipment component can open the door to a variety of exploitable vulnerabilities. Cloud computing and mobile application control have the potential to expand the threat surface to non-repudiation and firmware integrity challenges. Vendor clouds have access to hundreds of chargers, and if compromised, can scale the attack surface exponentially. The high power and voltage levels of xFC infrastructure (e.g., 400 kW at 1000- V DC) increase the hazards and ability to impact the grid and vehicles more than lower-power charging systems. Legacy communications systems and protocols could also put EV infrastructure at risk of cyberattacks requiring a robust patch management process. Communications networks link EVs and chargers to several stakeholders - including charging station operators, grid operators, vendors/manufacturers, and aggregators - who have both physical and network access to share information for control, monitoring, and analytics. Information in these networks that is vulnerable to compromise includes the state of charge, charging duration, payment information, electricity price, and load control. Analyzing and prioritizing these interconnections risks could help address cybersecurity related to data leakage and manipulation.

charging↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Probabilistic Modeling of Climate Change Impacts on Renewable Energy and Storage Requirements for NM's Energy Transition Act (SAND Report)

This report provides a study of the potential impacts of climate change on intermittent renewable energy resources, battery storage, and resource adequacy in Public Service Company of New Mexico’s Integrated Resource Plan for 2020 – 2040. Climate change models and available data were first evaluated to determine uncertainty and potential changes in solar irradiance, temperature, and wind speed in NM in the coming decades. These changes were then implemented in solar and wind energy models to determine impacts on renewable energy resources in NM. Results for the extreme climate-change scenario show that the projected wind power may decrease by ~13% due to projected decreases in wind speed. Projected solar power may decrease by ~4% due to decreases in irradiance and increases in temperature in NM. Uncertainty in these climate-induced changes in wind and solar resources was accommodated in probabilistic models assuming uniform distributions in the annual reductions in solar and wind resources. Uncertainty in battery storage performance was also evaluated based on increased temperature, capacity fade, and degradation in round-trip efficiency. The hourly energy balance was determined throughout the year given uncertainties in the renewable energy resources and energy storage. The loss of load expectation (LOLE) was evaluated for the 2040 No New Combustion portfolio and found to increase from 0 days/year to a median value of ~2 days/year due to potential reductions in renewable energy resources and battery storage performance and capacity. A rank-regression analyses revealed that battery round-trip efficiency was the most significant parameter that impacted LOLE, followed by solar resource, wind resource, and battery fade. An increase in battery storage capacity to ~25,000 – 30,000 MWh from a baseline value of ~14,000 MWh was required to reduce the median value of LOLE to ~0.2 days/year with consideration of potential climate impacts and battery degradation.

54 ENVIRONMENTAL SCIENCES↗

Impact of Lost Generation at the Glen Canyon Powerplant due to the Environmental Requirements for the Years 2024 to 2027

This report was prepared by Argonne National Laboratory (Argonne) and the National Renewable Energy Laboratory (NREL) in support of an economic and financial analysis conducted for the U.S. Department of Energy’s Western Area Power Administration (WAPA) of the loss in Glen Canyon power generation due to the environmental requirements for the years 2024 to 2027. WAPA markets electricity produced at hydroelectric facilities operated by the Bureau of Reclamation (Reclamation). The facilities known collectively as the Salt Lake City Area Integrated Projects (SLCA/IP) include dams equipped for power generation on the Colorado, Green, Gunnison, and Rio Grande rivers and on Plateau Creek in the states of Arizona, Colorado, New Mexico, Utah, and Wyoming.

13 HYDRO ENERGY↗

Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study

National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Synergies and trade-offs between storage, transmission, and sector coupling in high renewable energy systems

Energy storage, transmission, and sector coupling are some prominent flexibility solutions to support variable renewable energy (VRE) integration. However, investment cost uncertainties and public acceptance could hamper the deployment of these flexibility solutions. This raises questions about the development and cost-effectiveness of future energy systems, especially on how the dependence on local and cross-border solutions of flexibility would evolve if the uptake of these solutions is restricted. In this context, this paper identifies the synergies among flexibility options under restrictions on transmission expansion or increased costs of energy storage. It contributes to determining whether investments in energy storage and/or transmission expansion offer the least-cost transition and investigates the impact of sector coupling on these solutions. A long-term energy system planning and optimisation model towards 2050 is developed using the open-source energy system optimisation tool Balmorel, and a case study of the countries surrounding the Baltic Sea and the North Sea is established. Five cases with restrictions imposed on transmission expansion and higher energy storage technology costs are analysed at different levels of sector coupling. The results highlight the importance of transmission expansion at all levels of sector coupling. As the level of sector coupling increases, uncertainties around the cost of energy storage drive the least-cost pathways. Optimal investment solutions are found to have a mix of transmission and energy storage in capacity expansion at all levels of sector coupling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Pumped Thermal Energy Storage Using Low-Cost Particles and a Fluid Bed Heat Exchanger for Maximum Power Efficiency

Robust, efficient, cost-effective long-duration electricity storage (LDES) solutions can enhance grid resiliency, support existing transmission and distribution infrastructure, and enable a greater share of low-cost, variable alternative energy sources to penetrate the market. To meet this need, the project team at the National Renewable Energy Laboratory developed a transformative LDES system based on pumped thermal energy storage (TES) using low-cost particles and a fluid bed heat exchanger for maximum power efficiency (PUMP). The PUMP system is composed of high-temperature, low-cost particle TES coupled with an advanced pressurized fluid bed heat exchanger (PFB HX) that supports a high-efficiency pumped thermal energy storage (PTES) system integrated with concentrating solar thermal power (CSP). The PUMP project developed and de-risked a PFB HX and particle CSP system intended to be integrated with reversible turbomachinery and a modeling tool to assess PTES cost and performance.

14 SOLAR ENERGY↗

Hydroelectric Power and Hydrogen Production Integration

Hydropower-based hydrogen production could introduce opportunities for new revenue streams for hydropower plants, including from energy storage and regeneration as well as from sale of the hydrogen product to external markets. Hydrogen-based energy storage and regeneration could also help support Idaho Power’s decarbonization goals by decreasing dependence on fossil-based peaking power plants. Additionally, integration of hydrogen production with hydropower generation could help address the issue of low dissolved oxygen river water conditions that commonly accompany hydropower plant operations by utilizing the oxygen byproduct from an electrolytic hydrogen production process as a resource for mitigation of low dissolved oxygen water conditions. Comprehensive techno-economic analysis of the hybrid hydroelectric and hydrogen energy storage system has revealed critical insights into the pathways and considerations for optimizing the economic value and environmental benefits of such systems. Among the three identified pathways of natural gas blending, regeneration, and direct sale of hydrogen, the direct sale of hydrogen emerges as the most profitable, particularly given the current pricing dynamics of hydrogen and electricity. However, as we anticipate a future grid characterized by higher renewable energy penetration, the landscape may evolve, featuring lower average electricity prices, heightened fluctuations, and more significant seasonal variations. Consequently, the attractiveness of electricity regeneration through hydrogen and the benefits of long-duration hydrogen storage are expected to increase substantially in such a dynamic energy scenario. The careful selection of component sizes within the hybrid system proves to be paramount for ensuring cost-effectiveness. Notably, the size of the hydrogen market has emerged as a critical determinant for the optimal size of the electrolyzer. Hydrogen storage should be sized to meet energy shifting requirements. The appropriate size of the fuel cell/microturbine generator hinges on the shape of electricity prices and the available revenue streams derived from participating in grid services. Striking the right balance among these components is essential for maximizing the overall efficiency and profitability of the hydrogen facility. Furthermore, the by-product of electrolysis, namely oxygen, introduces an additional dimension to the system's functionality. The oxygen generated can be effectively utilized for dissolved oxygen (DO) mitigation, particularly with larger electrolyzer sizes capable of satisfying the complete oxygen demand for this purpose. While the economic benefits derived from saved oxygen purchase costs may be relatively modest compared to other revenue streams, the environmental advantages of repurposing oxygen for DO mitigation could help Idaho Power meet their environmental obligations. In addition to the identified factors shaping the viability of hybrid hydrogen production and hydroelectric generation, it is noteworthy that the integration of hydrogen energy storage offers a unique advantage during unusually wet years. In such periods of increased water inflow, the hydrogen storage capacity serves as a valuable supplement to the reservoir. By utilizing hydrogen energy storage as a complementary reservoir, the system gains flexibility in reservoir management when dealing with fluctuations in water availability.

08 HYDROGEN↗

Assessing the levelized cost of energy in South Korea

This study evaluates the levelized cost of energy (LCOE) for various energy technologies in the Republic of Korea (Korea) from 2023 to 2050, highlighting cost trajectories and potential crossovers among competing technologies. The analysis projects that, based on our set of assumptions, utility-scale photovoltaic systems achieve lower LCOEs than nuclear by 2030, while fixed offshore wind is expected to become cost-competitive with coal-fired generation around the same time. Floating offshore wind is projected to reach cost parity with coal in the late 2030s. Co-firing with natural gas and green hydrogen is identified as the highest-cost generation option due to high natural gas and green fuel costs and declining capacity utilization. This study further examines the potential for hybrid systems that integrate renewable energy with energy storage to serve as flexible, cost-effective, zero-emission alternatives to green hydrogen-based generation. Spatial LCOE assessments indicate that near-shore offshore wind sites may achieve lower costs despite modest capacity factors, contingent on site-specific factors such as grid integration and social acceptance. The findings indicate that renewable energy technologies are expected to experience continued cost declines, with solar photovoltaic becoming the most competitive energy source in Korea by 2030–2035. Incorporating social costs accelerates this shift from conventional alternatives.

Green hydrogen↗

A real-time multiphysics model of a pressurized solid oxide electrolysis cell (SOEC) for cyber-physical simulation

Solid oxide electrolysis cells (SOEC) can play important roles in integrated energy systems (IES) as the hydrogen production hub and the resilience energy hub. When tied to a microgrid with high renewable penetration, the SOEC is subjected to rapid load transitions in response to the intermittent renewable generations that occur not only in diurnal cycles but also in short timeframes (e.g., sub-minute). The cyber-physical simulation approach can derisk operability research but requires a real-time dynamic SOEC model. In the present work, a real-time multiphysics model for pressurized SOEC is developed and validated in the pressure range from 1.4 to 8bar. Further, the accuracy of the single repeating unit (SRU) assumption in SOEC stack simulation is quantified. A guidance of more than 45 cells in one SOEC stack is recommended to safely apply the SRU assumption. Modeling results suggest that at a given current density, more power is consumed by SOEC at elevated operating pressures. The anode air and cathode stream have major impacts on thermal management, highlighting the potential benefit of integrating SOEC with other thermal processes in IES. To achieve high hydrogen production efficiency, the SOEC could operate at the maximum endothermic point to maximize the use of thermal energy. The real-time execution of the developed SOEC model is also demonstrated, which only takes 0.1% of the fixed time step of 5ms. The developed model establishes the basis for cyber-physical simulation of SOEC hybrid systems.

25 ENERGY STORAGE↗